Thanks for your responses. Yes, I was looking for the weighted average.
rate = [14.424, 14.421, 14.417, 14.413, 14.41]
amount = [3058.0, 8826.0, 56705.0, 30657.0, 12984.0]
I want the weighted average of the top list based on each item of the bottom list.
So, if the first bottom-list item is small (such as 3,058 compared to the total 112,230), then the first top-list item should have less of an effect on the top-list average.
Here is some of what I have tried. It gives me an answer that looks right, but I am not sure if it follows what I am looking for.
for g in range(len(rate)):
rate[g] = rate[g] * (amount[g] / sum(amount))
rate = sum(rate)
EDIT: After comparing other responses with my code, I decided to use the zip code to keep it as short as possible.
You could use numpy.average
to calculate weighted average.
In [13]: import numpy as np
In [14]: rate = [14.424, 14.421, 14.417, 14.413, 14.41]
In [15]: amount = [3058.0, 8826.0, 56705.0, 30657.0, 12984.0]
In [17]: weighted_avg = np.average(rate, weights=amount)
In [19]: weighted_avg
Out[19]: 14.415602815646439